docs/STREAMLIT_DEPLOYMENT.md

🚀 Deploy to Streamlit Cloud - Step by Step

✅ Ready to Deploy!

I've prepared all the files you need for Streamlit Cloud deployment. Here's exactly what to do:

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📋 Step 1: Prepare Your GitHub Repository

1.1 Create/Update GitHub Repository

# If you haven't already, initialize git in your project
git init

# Add all files
git add .

# Commit changes
git commit -m "Add Streamlit Cloud deployment files"

# Add your GitHub repository as remote (replace with your repo URL)
git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO_NAME.git

# Push to GitHub
git push -u origin main

1.2 Verify Required Files Are Present

Make sure these files exist in your repository:

• ✅ streamlit_app.py (main entry point)
• ✅ cloud_backend.py (mock translation service)
• ✅ requirements.txt (dependencies)
• ✅ .streamlit/config.toml (Streamlit configuration)

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📋 Step 2: Deploy on Streamlit Community Cloud

2.1 Go to Streamlit Cloud

1. Visit: https://share.streamlit.io
2. Click "Sign in with GitHub"
3. Authorize Streamlit to access your repositories

2.2 Create New App

1. Click "New app"
2. Select your repository from the dropdown
3. Choose branch: main
4. Set main file path: streamlit_app.py
5. Click "Deploy!"

2.3 Wait for Deployment

• First deployment takes 2-5 minutes
• You'll see build logs in real-time
• Once complete, you'll get a public URL

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🌐 Step 3: Access Your Live App

Your app will be available at:

https://YOUR_USERNAME-YOUR_REPO_NAME-streamlit-app-HASH.streamlit.app

Example:

https://karti-bharatmlstack-streamlit-app-abc123.streamlit.app

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🎯 Step 4: Test Your Deployment

4.1 Basic Functionality Test

1. Open your live URL
2. Try translating: "Smartphone with 128GB storage"
3. Select languages: English → Hindi, Tamil
4. Check results: Should show realistic translations
5. Test history: Check translation history page
6. Verify analytics: View analytics dashboard

4.2 Features to Demonstrate

✅ Product Translation: Multi-field translation ✅ Language Detection: Auto-detect functionality
✅ Quality Scoring: Confidence percentages ✅ Correction Interface: Manual editing capability ✅ History & Analytics: Usage tracking

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🔧 Step 5: Customize Your Deployment

5.1 Custom Domain (Optional)

• Go to your app settings on Streamlit Cloud
• Add custom domain if you have one
• Update CNAME record in your DNS

5.2 Update App Metadata

Edit your repository's README.md:

# Multi-Lingual Catalog Translator

🌐 **Live Demo**: https://your-app-url.streamlit.app

AI-powered translation for e-commerce product catalogs using IndicTrans2.

## Features
- 15+ Indian language support
- Real-time translation
- Quality scoring
- Translation history
- Analytics dashboard

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📊 Step 6: Monitor Your App

6.1 Streamlit Cloud Dashboard

• View app analytics
• Monitor usage stats
• Check error logs
• Manage deployments

6.2 Update Your App

# Make changes to your code
# Commit and push to GitHub
git add .
git commit -m "Update app features"
git push origin main

# Streamlit Cloud will auto-redeploy!

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🎉 Alternative: Quick Test Locally

Want to test the cloud version locally first?

# Run the cloud version locally
streamlit run streamlit_app.py

# Open browser to: http://localhost:8501

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🆘 Troubleshooting

Common Issues:

1. Build Fails:

# Check requirements.txt
# Ensure all dependencies have correct versions
# Remove any unsupported packages

2. App Crashes:

# Check Streamlit Cloud logs
# Look for import errors
# Verify all files are uploaded to GitHub

3. Slow Loading:

# Normal for first visit
# Subsequent loads are faster
# Consider caching for large datasets

Getting Help:

• Streamlit Docs: https://docs.streamlit.io/streamlit-community-cloud
• Community Forum: https://discuss.streamlit.io/
• GitHub Issues: Check your repository issues

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🎯 For Your Interview

Demo Script:

1. Share the live URL: "Here's my live deployment..."
2. Show translation: Real-time product translation
3. Highlight features: Quality scoring, multi-language
4. Discuss architecture: "This is the cloud demo version..."
5. Mention production: "The full version runs with real AI models..."

Key Points:

• ✅ Production deployment experience
• ✅ Cloud architecture understanding
• ✅ Real user interface design
• ✅ End-to-end project delivery

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🚀 Ready to Deploy?

Run these commands now:

# 1. Push to GitHub
git add .
git commit -m "Ready for Streamlit Cloud deployment"
git push origin main

# 2. Go to: https://share.streamlit.io
# 3. Deploy your app
# 4. Share the URL!

Your Multi-Lingual Catalog Translator will be live and accessible worldwide! 🌍